Chen Et Al Methods of Estimating Evapotranspiration

8/12/2019 Chen Et Al Methods of Estimating Evapotranspiration

1/10

CLIMATE RESEARCH

Clim ResVol. 28: 123132, 2005 Published March 16

1. INTRODUCTION

Evapotranspiration (ET) is an important componentof the hydrological cycle and is essential for under-

standing land surface processes in climatology. In

ecosystem and agriculture studies productivity is

closely linked to actual ET. In practice, estimation of

actual ET is often made by using information about

potential ET and soil moisture (e.g. Dyck 1983). The

potential ET, formally defined as wet-surface evapora-

tion, is the ET governed by available energy and

atmospheric conditions, as the water availability is not

a limiting factor. Thus, potential ET is a function of

atmospheric forcing and surface types. In order to

remove the influence of surface types, the concept of

reference evapotranspiration (ET0) was introduced to

study the evaporative demand of the atmosphere inde-pendent of crop type, crop development and manage-

ment practices (Allen et al. 1998). ET0 is defined as the

potential ET of grass. As water is abundantly available

at the reference evapotranspiring surface, soil factors

do not affect ET0. Relating ET0 to a specific surface

(grass) rovides a reference from which ET for other

surfaces can be estimated (Doorenbos & Pruitt 1977,

Allen et al. 1998).

There is a long history in the study of ET and relating

it to meteorological variables, and the earliest method

dates back to the beginning of the 19th century (e.g.

Inter-Research 2005 www.int-res.com*Email: [email protected]

Comparison of the Thornthwaite method and pan

data with the standard Penman-Monteith estimatesof reference evapotranspiration in China

Deliang Chen1,2,*, Ge Gao1, 2, Chong-Yu Xu3, Jun Guo4, Guoyu Ren2

1Regional Climate Group, Earth Sciences Centre, Gothenburg University, PO Box 460, 405 30 Gothenburg, Sweden2Laboratory for Climate Studies/National Climate Center, China Meteorological Administration,

No. 46 Zhongguancun Nandajie, Haidian, Beijing 100081, China3Dept of Earth Sciences, Hydrology, Uppsala University, Villavgen 16, 752 36 Uppsala, Sweden

4Tianjin Meteorological Bureau, 100 Qixiangtai Road, Hexi District, Tianjin 300074, China

ABSTRACT: Various methods are available to estimate reference evapotranspiration (ET0) from stan-

dard meteorological observations. The Penman-Monteith method is considered to be the most phys-ical and reliable method and is often used as a standard to verify other empirical methods. This study

estimates and compares the monthly ET0 calculated by 3 methods at 580 Chinese stations over the

last 50 yr. The Penman-Monteith method is used here as a reference, and its spatial and temporal dif-

ferences with the Thornthwaite method and pan measurement are evaluated. The results show that:

(1) in terms of spatial difference, the Thornthwaite estimates show different regional patterns, while

pan measurements display a consistent regional pattern; (2) the temporal variability of ET0 is muchbetter represented by pan measurements than by the Thornthwaite estimates. Overall, pan measure-

ments are more useful than the Thornthwaite estimates if appropriate pan coefficients are deter-

mined. The Thornthwaite method only considers the temperature and latitude and gives unreliable

results under dry conditions, e.g. in NW China. With reference to the Penman-Monteith estimates,the correction factors (pan coefficients) of pan measurements for the whole of China, and the regionalaverages over the 10 major drainage basins are determined. The average value lies between 0.6 and

0.8, although a seasonal and regional difference is present.

KEY WORDS: Reference evapotranspiration Water evaporation Penman-Monteith Thornthwaite

Pan China

Resale or republication not permitted without written consent of the publisher


2/10

Clim Res 28: 123132, 2005

Brutsaert 1982). Since then, many methods have been

developed, which can be grouped into 6 categories

(e.g. Xu & Singh 2002): (1) water budget methods

(e.g. Guitjens 1982); (2) mass-transfer methods (e.g.

Harbeck 1962); (3) combination methods (e.g. Penman

1948, Monteith 1965), for the FAO Penman-Monteithmethod see Allen et al. (1998); (4) radiation-based

methods (e.g. Priestley & Taylor 1972); (5) tempera-

ture-based methods (e.g. Thornthwaite 1948, Blaney-

Criddle 1950); and (6) pan evaporation methods (e.g.

Allen et al. 1998). In general, techniques for estimating

ET0 are based on one or more atmospheric variables,

such as air temperature, solar or net radiation and

humidity, or on some measurements related to these

variables, like pan evaporation. Certain of these meth-

ods are accurate and reliable; others provide only a

rough approximation. Most of the methods were

developed for use in specific studies and are most

appropriately applied to climates similar to that wherethey were developed (Chattopadhyay & Hulme 1997).

The Penman-Monteith method is recommended as

the sole standard by the FAO (Allen et al. 1998).

The classic Penman-Monteith method combines both

energy and mass balances to model ET0. It is based on

fundamental physical principles, which guarantee the

universal validity of the method. However, it needs a

number of meteorological variables which may not

be available everywhere. In this study, the Penman-

Monteith method is used as a standard to evaluate the

performance of other methods.

Since air temperature is a widely available variable,

the Thornthwaite method, a simple method developed

by Thornthwaite (1948) that uses only air temperature

and latitude of the site to estimate ET0, is widely used

in the literature. However, because it can be com-

puted from temperature and latitude, it has been one

of the most misused empirical equations generating

inaccurate estimates of evapotranspiration for arid and

semiarid irrigated areas (Jensen 1973). Although the

method is not recommended for use in areas that are

not climatically similar to the east-central USA, where

it was developed (Jensen 1973), it has also been used

in China by some researchers (e.g. Ma & Fu 2001). In

this study, the applicability of the Thornthwaitemethod to climatic conditions in China is evaluated in

view of the advantage that the method offers in calcu-

lating ET0 by using temperature alone, which is the

most commonly determined meteorological variable in

this part of the world.

The pan measurement method uses pan evaporation

to estimate ET0 and is another common method, espe-

cially in Asian countries. The evaporation rate from

pans filled with water is easily obtained. In the absence

of rain, the amount of water evaporated (mm d1) cor-

responds to the decrease in water depth. Pans provide

a measurement of the integrated effect of radiation,

wind, temperature and humidity on the evaporation

from an open-water surface. Although the pan

responds in a similar fashion to the same climatic fac-

tors affecting crop transpiration, several factors pro-

duce differences between loss of water from a watersurface and that from the surface of crops (e.g. Allen et

al. 1998). Storage of heat within the pan can be appre-

ciable and may cause significant evaporation during

the night, while most crops transpire only during the

daytime. There are also differences in turbulence, tem-

perature and humidity of the air immediately above

the respective surfaces. Heat transfer through the sides

of the pan affects the energy balance. However, the

pan has proved its practical value and has been widely

used to estimate ET0. Applying empirical coefficients

to relate pan evaporation to ET0 for periods of 10 days

or longer may be warranted (Allen et al. 1998). In

China, the network for pan measurements is muchdenser than that of meteorological stations, but in

order to make good use of pan evaporation data, spa-

tial and seasonal variations of the pan coefficient need

to be determined with accuracy. This study evaluates

the performance of the pan measurement method and,

by comparing it with Penman-Monteith ET, the sea-

sonal and spatial variations of the pan coefficient are

determined.

In China, many studies have attempted to estimate

ET0 (Zhu &Yang 1955, Lu et al. 1965, Qian & Lin 1965,

Gao et al. 1978), often for calculating the humidity

index for climate regionalization. However, many of

the investigations are regional in nature. Furthermore,

only 1 of the methods is usually used in a region or at

a small number of selected stations over the country

(e.g. Axel 2000); comparison of different methods at

regional and national scales is rare.

The objectives of this study are: (1) to estimate ET0for the whole of China by using the Penman-Monteith

and Thornthwaite methods and pan measurements;

(2) to compare the Thornthwaite estimates and pan

measurements with the Penman-Monteith estimates;

and (3) to determine the extent to which the Thornth-

waite method and the pan measurement data can be

useful in estimating ET0 for various parts of China.

2. DATA AND METHODS

2.1. Data on climate and water evaporation

Monthly climate data from 1951 to 2000 at 580 mete-

orological stations (Fig. 1) in China were used in this

study. They include the data needed to calculate ET0,

namely mean air temperature, mean maximum and

minimum temperature, mean sunshine duration, wind

124


3/10

Chen et al.: Methods of estimating evapotranspiration

speed and humidity, as well as the monthly water

evaporation in a pan of 20 cm diameter. The time series

of most stations span more than 40 yr; those from only

10 and 1% of stations are between 35 and 40 yr for pan

and monthly mean temperature, respectively.

2.2. Penman-Monteith method

According to the FAO (Allen et al. 1998), the Penman-

Monteith method for ET0 (mm d1) can be expressed as:

where Rn is the net radiation at the crop surface

(MJ m2 d1), G is the soil heat flux density (MJ m2

d1), Tis the air temperature at 2 m height (C), u2 is

the wind speed at 2 m height (m s1), es is the saturation

vapor pressure (kPa), ea is the actual vapor pressure(kPa), es ea is the saturation vapor pressure deficit

(kPa), is the slope vapor pressure curve (kPa C1)

and is the psychrometric constant (kPa C1).

The computation of all data required for the calcula-

tion of ET0 followed Chapter 3 of FAO Paper 56 (Allen

et al. 1998). The only difference is that in calculating

solar radiation using Eq. (35) in Allen et al. (1998), the

recommended values for the parameters as and bs were

not used; instead, we chose to use the regional values

determined by Zhu (1982), as they were based on mea-

surements in China. The constants were given for 4

regions: NE China, east China, NW China and the

Tibetan Plateau.

2.3. Thornthwaite method

Thornthwaite (1948) correlated mean monthly tem-

perature with ET, as determined from water balance

for valleys in the eastern USA where sufficient mois-

ture water was available to maintain active transpira-tion. The Thornthwaite formula for monthly ET0 (mm)

is:

ET0 = 16 d(10T/ I)a

Where T is the mean temperature for the month (in

C), I is the annual thermal index, i.e. the sum of

monthly indices i [i = (T/5) 1.514], d is a correction

factor which depends on latitude and month, and a is

0.49 + 0.0179 I 0.0000771 I2 + 0.000000675 I3.

2.4. Pan evaporation

There are different pans for measuring evaporation,

and the one with a diameter of 20 cm and a height of

10 cm is used in China. It is made of metal and has a

veil on it. It is installed 70 cm above the ground. The

water level is measured at 20:00 h Beijing time every

day. A base level of 20 mm water depth is set daily. The

evaporation is equal to base + rainfall remains. Since

the 1980s, another type of pan (E-601), 61.8 cm in

diameter, has been used in China. Parallel measure-

ments at selected stations in China show that the small

pan and the E-601 pan give different results; however,

the difference is fairly systematic so that a correction

factor has been established (Liu et al. 1998). From

1995, the E-601 pan was replaced by another pan

(E-601B) made of glass fiber reinforced plastics, and

until June 1998 the entire network of about 600

stations in China had been equipped with this type of

pan. The values observed using this pan are closer to

actual evaporation from small and middle-sized bodies

of water than those of the other pans. A coefficient for

conversion from the small evaporation pan to the

E-601B pan in China was obtained by Ren et al. (2002).

2.5. Evaluation

Due to its solid physical basis, the ET0 estimated by

the Penman-Monteith method is considered the most

reliable and used as the reference to which the other

2 estimates are compared. The comparison is made for

each station on seasonal and annual bases. For the

spatial distribution the following 3 measures are given:

(1) relative bias, (2) relative root mean square error

(RMSE), and (3) correlation coefficient. Note that the

relative biases and errors are normalized against the

means of the Penman-Monteith estimates.

ETn s a

0

900273 2

0 408

1 0 3=

( ) + ( )

+ ++

.

.

R G u e e T

44 2u( )

125

Fig. 1. Meteorological stations used in this study and the 10drainage basins. Numbers denote the 10 drainage basins: 1: Song

Hua River; 2: Liao River; 3: Hai River; 4: Yellow River; 5: HuaiRiver; 6: Yangtze River; 7: SE rivers; 8: Pearl River; 9: SW rivers;

10: NW rivers


4/10

Clim Res 28: 123132, 2005126

Fig. 2. Seasonal and annual mean reference evapotranspiration(ET0, mm) estimated by the Penman-Monteith method

Spring Summer

Autumn Winter

Annual


5/10


The biases and RMSE summarize the error statistics

over the whole period and give an averaged difference

in 2 different ways. In reality, variation from year to

year is large, and how this variation is reflected in the

estimate gives a good indication about how the method

works. Furthermore, the temporal variation of evapo-ration is considered as an important indicator of

climate change (Peterson et al. 1995, Brutsaert &

Parlange 1998).

3. RESULTS AND DISCUSSION

3.1. Penman-Monteith method

Fig. 2 shows the seasonal and annual ET0 over

China, estimated from the Penman-Monteith method.

In spring, there is a great gradient of air humidity over

China. The distribution pattern of the humidity resem-bles that of ET0, indicating the important role played

by air humidity during this season. In summer the spa-

tial differences are relatively small, while the absolute

values are relatively high due to the strong solar radia-

tion in the south and the low humidity values in the

north. The maximum value occurs in the NW part of

the country where the summer monsoon has a negligi-

ble influence. Autumn reveals a fairly homogeneous

spatial distribution, while winter shows a clear south-

north gradient, indicating the dominant role of radia-

tion. The annual distribution shows low ET in the

middle of the Yangtze River Basin and in NE China

and high ET in NW and SW China.

3.2. Thornthwaite method

An examination of the seasonal and annual esti-

mates of the Thornthwaite in comparison with the

Penman-Monteith estimates shows great differences,

especially on a regional basis. Fig. 3 shows the

annual biases with the Penman-Monteith method.

Although not shown, on a seasonal basis the Thorn-

thwaite method overestimates the ET0 in SE China

and underestimates it in other parts of China inspring, summer and autumn, whereas there is an

underestimation in winter over the entire country.

Since the Thornthwaite method is an empirical

method based on observations made in the eastern

USA, its application under Chinese climatic condi-

tions may be problematic, at least with its original

parameter values. The annual bias indicates that the

Thornthwaite method overestimates ET0 over the

monsoon affected areas where climate is relatively

humid, while for arid and semiarid parts of China it

produces an underestimation.

Fig. 4 shows the distribution of annual relative RMSE

of the Thornthwaite estimates. The annual relative

RMSE ranges from 3.8 to 65.7% across China.

The correlation coefficients between the 2 estimates

on an annual basis are shown in Fig. 5. On a seasonal

basis (not shown) there exists a better agreement

during spring and summer than during winter and

autumn. The regional differences are fairly large over

all 4 seasons. On average, there is a moderate correla-

tion between the two, indicating that the Thornthwaite

method only accounts for a small part of the temporal

variability over China. Furthermore, on an annual

basis, the NW and part of inner Mongolia show a neg-

127

Fig. 3. Annual relative bias (%) of reference evapotranspira-tion estimated by the Thornthwaite method compared with

the Penman-Monteith method

Fig. 4. Annual relative RMSE (%) of reference evapotranspi-ration estimated by the Thornthwaite method compared with

the Penman-Monteith method


6/10

Clim Res 28: 123132, 2005

ative correlation. This implies that the Thornthwaite

method does not follow the change in the Penman-

Monteith estimates with time, which disqualifies use of

the former in climate change studies in China.

3.3. Pan measurement

Since pan measurements are made for the water sur-

face of a relatively small area, a large positive bias is

expected. Fig. 6 shows a consistent regional picture of

the bias with high values in northern and NW areas

and low values in the south. This is certainly a reflec-

tion of the different humidity conditions across China.

The annual estimates have a relative bias from 21.4%

in the south to 155.1% in the north and NW.

Due to the consistent positive bias over all seasons

and regions, a large relative RMSE is expected. Fig. 7displays the annual relative RMSE for pan measure-

ment, which to a large extent is caused by the positive

bias showed in Fig. 6. Pan measurements in part of

the south are fairly close to the Penman-Monteith

estimates on an annual basis.

Because the bias is consistently positive over the

entire country, the deviation of pan measurement from

the Penman-Monteith estimate is fairly systematic over

various regions. Seasonal (not shown) and annual

correlation coefficients (Fig. 8) are all positive, which

shows that temporal variation in pan measurement

follows that of the Penman-Monteith estimates. For

most regions and seasons the correlations are fairlyhigh, indicating that the pan measurement simulates

the change in all relevant meteorological conditions

fairly well. This may not be surprising as pan evapora-

tion measures the integrated effect of radiation, wind,

temperature and humidity on the evaporation from an

open-water surface.

The high correlation and systematic difference make

pan measurement a suitable substitute for the Pen-

man-Monteith estimates. In fact, this kind of measure-

ment has been widely used (e.g. Guo et al. 2002).

Typically, pan measurements are directly used, to-

gether with precipitation, as the inputs to a hydro-

logical model, and then the model is calibrated against

other observations to get suitable model parameters. It

should be noted that the values of the related para-

128

Fig. 6. Annual relative bias (%) of reference evapotranspira-

tion estimated by pan measurement compared with thePenman-Monteith method

Fig. 5. Annual correlations of reference evapotranspirationestimates from the Thornthwaite method with those of the

Penman-Monteith method

Fig. 7. Annual relative RMSE (%) of reference evapotrans-piration estimated by pan measurement compared with the

Penman-Monteith method


7/10


meters calibrated in this way will be biased from the

true values. Ideally, the input to the model should be

the pan measurement data multiplied by the pan coef-

ficient as obtained in this study so that the parameters

determined will be reasonable and the model simula-

tion realistic. In addition, some other applications, such

as water requirement estimates for a crop, require the

ET0 as defined by the FAO. Therefore, a correction of

the pan measurement by multiplying it by the pan

coefficient would also be necessary to give a better

estimate of ET0.

The correction factor (pan coefficient), defined as the

ratio of the Penman-Monteith estimate to that of the

pan measurement, is calculated for each station and

month and interpolated to give a regional distribution

pattern for the whole of China. Fig. 9 shows the ratios

on seasonal and annual bases. There is some varia-

tion in the ratio across China. As a

whole, the ratio varies between 0.4 and

0.8 with an average of about 0.6. This

spatially interpolated seasonal correc-

tion factor can be used to convert pan

evaporation measurements into ET0 inplaces where there are no meteoro-

logical data available to calculate ET0.

3.4. Summary

For hydrological applications, the

drainage basin is the unit to consider

and the characteristic of the time series

is of importance. The long-term varia-

tion properties of pan measurements

and ET0 estimated by the Penman-Monteith and

Thornthwaite methods, as measured by the temporal

trend and the correlation coefficient of the linear trend,

are summarized in Table 1 for the 10 major catchments

in China. In Table 1 the trend is the slope of the linear

regression, with evaporation as the dependent vari-able and time as the independent variable. Table 1

shows that: (1) According to the Penman-Monteith

estimates, evapotranspiration in 3 catchments has an

increasing trend, of which 1 is significant (Song Hua in

NE China); the remaining catchments have a decreas-

ing trend, of which 4 are significant. (2) In 9 out of 10

catchments the pan estimates show the same trend

direction as those of the Penman-Monteith method but

are greater in magnitude in most cases. The only

exception is the Yellow River Basin, where a decreas-

ing trend is found with pan measurements. (3) The

Thornthwaite estimate gives an increasing trend for all

the catchments which is very different from the other 2methods. The reason is that in most regions of China

air temperature has been increasing during recent

decades, while wind speed and solar radiation have

been significantly decreasing during the same period

(e.g. Xu et al. 2004). Accordingly, ET calculated by the

Thornthwaite method, which uses only temperature as

input data, shows an increasing trend for all catch-

ments, while the Penman-Monteith method and pan

evaporation provide a measurement of the integrated

effect of radiation, wind, temperature and humidity.

Table 2 gives the relative biases and RMSE and

the correlation coefficient between the Thornthwaite

method, and pan and Penman-Monteith estimates:

(1) For the long-term average values there is a system-

atic deviation between pan evaporation and Penman-

Monteith evapotranspiration, which resulted in a con-

sistent bias between the 2 estimates. The correlation

coefficient between the 2 estimates is quite high and

significant. Thus, pan measurement can be used to

129

Fig. 8. Annual correlations of reference evapotranspiration

estimates from pan measurement with those of the Penman-Monteith method

Table 1. Long-term trend of reference evapotranspiration (ET0, mm yr1)

estimated by the Penman-Monteith and Thornthwaite methods and pan eva-poration. R: correlation coefficient of the linear trend; *statistically significant

at 5% level

Penman-Monteith Thornthwaite PanTrend R Trend R Trend R

1 Song Hua River 0.99 0.38* 1.15 0.68* 1.49 0.25

2 Liao River 0.32 0.11 0.97 0.53* 0.16 0.023 Hai River 0.67 0.21 1.11 0.55* 3.33 0.36*

4 Yellow River 0.05 0.02 0.63 0.49* 3.04 0.40*5 Huai River 0.52 0.15 0.69 0.35* 4.51 0.47*

6 Yangtze River 1.11 0.47* 0.17 0.15* 1.76 0.32*7 Southeast rivers 1.11 0.34* 0.44 0.32* 1.39 0.24*

8 Pearl River 1.25 0.47* 0.33 0.38* 2.12 0.35*9 Southwest rivers 0.14 0.08 0.45 0.54* 0.84 0.17*

10 Northwest rivers 1.57 0.63* 0.67 0.54* 3.11 0.42*


8/10

Clim Res 28: 123132, 2005130

Fig. 9. Seasonal and annual ratio of reference evapotranspira-tion (ET0) estimation by the Penman-Monteith method to that

of pan measurement (pan coefficient)

Annual

Autumn

Spring Summer

Winter


9/10


represent the Penman-Monteith evapotranspiration

provided that a correction is made by multiplying it

by the pan coefficient. (2) The difference between

the Thornthwaite and Penman-Monteith estimates as

measured by the bias and RMSE shows no consistent

relationship, and the correlation coefficient between

the 2 estimates is much lower than for pan evapora-

tion. This means that a large unpredictable error is

expected if the Thornthwaite method is used to esti-

mate ET0 in China.

4. CONCLUSIONS

(1) ET0 estimated by the Penman-Monteith method

as recommended by the FAO shows large regional

differences and seasonal variation over China.

(2) The Thornthwaite method overestimates ET0 in

SE China where ET0 is low, and underestimates it in

northern and NW parts where ET0 is high. In addition,

this method does not follow the temporal variation

well. The reason is that the Thornthwaite method uses

131

Table 2. Seasonal and annual statistics of reference evapotranspiration (ET0) estimates from the Thornthwaite and pan methodsin comparison to the Penman-Monteith method. The relative bias and RMSE are calculated in relation to the Penman-Monteith

estimate (%). Correlation coefficient (R) is the correlation between the seasonal/annual values of the Thornthwaite method, andpan and Penman-Monteith methods. Bias(%) = Bias/ETPenman-Monteith; RMSE(%) = RMSE/ETPenman-Monteith; Ratio = pan coefficient =

ETPenman-Monteith / ETpan or Thornthwaite;xnot statistically significant at 5% level

Thornthwaite PanBias (%) RMSE R Ratio Bias (%) RMSE R Ratio

1 Song Hua River Spring 48.7 49.2 0.62 1.96 109.10 110.10 0.91 0.48Summer 29.9 30.3 0.64 0.77 69.9 70.6 0.95 0.59Autumn 39.8 40.6 0.28 1.67 71.3 72.1 0.89 0.59Winter 100.00 101.30 72.6 78.6 0.56 0.59Annual 13.3 13.9 0.58 1.15 82.5 82.9 0.86 0.55

2 Liao River Spring 46.3 46.7 0.42 1.87 109.00 109.70 0.91 0.48Summer 35.7 36.2 0.59 0.74 69.5 70.3 0.97 0.59Autumn 33.2 33.6 0.40 1.50 75.2 75.6 0.87 0.57Winter 100.00 100.80 0.05x 648.0000 71.9 73.9 0.76 0.59Annual 14.8 15. 5 0.50 1.17 83.6 83.9 0.89 0.55

3 Hai River Spring 37.8 38.4 0.48 1.61 111.00 112.10 0.93 0.48Summer 36.3 36.8 0.57 0.73 76.0 77.0 0.95 0.57Autumn 24. 7 25.7 0.14x 1.33 73.3 74.1 0.95 0.58Winter 99.4 100.10 0.30 239.5900 72.4 74.0 0.90 0.58Annual 11.4 12.4 0.32 1.13 86.3 86.8 0.93 0.54

4 Yellow River Spring 43.8 44.2 0.46 1.78 108.70 109.30 0.91 0.48Summer 8.9 9.7 0.60 0.92 83.1 83.8 0.91 0.55Autumn 36.8 37.5 0.18x 1.59 70.4 71.5 0.96 0.59Winter 99.2 99.6 0.64 162.9100 74.1 75.3 0.94 0.58Annual 25.9 26.2 0.46 1.35 87.5 87.9 0.83 0.53

5 Huai River Spring 28.4 29.3 0.65 1.40 88.7 90.0 0.90 0.53Summer 50.6 50.9 0.67 0.66 64.0 64.9 0.97 0.61Autumn 10.8 13.6 0.11x 1.12 60.8 61.9 0.94 0.62Winter 94.2 94.8 0.27x 27.690 62.0 64.1 0.92 0.62Annual 1.6 4.8 0.53 1.02 70.1 70.7 0.91 0.59

6 Yangtze River Spring 9.7 10.3 0.64 1.11 71.8 72.2 0.91 0.58Summer 46.5 46.7 0.80 0.68 55.6 56.1 0.93 0.64Autumn 0.6 6.4 0.20x 1.00 50.2 50.8 0.93 0.67Winter 76.4 76.6 0.36 4.40 68.9 69.4 0.87 0.59Annual 5.8 6.7 0.45 0.95 59.5 59.8 0.90 0.63

7 Southeast rivers Spring 5.27 8.5 0.61 0.95 59.1 59.7 0.93 0.63Summer 56.8 57.1 0.74 0.64 54.0 54.6 0.92 0.65

Autumn 7.4 11.6 0.09

x

0.93 58.5 59.1 0.95 0.63Winter 67.2 68.0 0.13x 3.20 55.1 56.1 0.95 0.65Annual 15.3 16.0 0.40 0.87 56.7 56.9 0.89 0.64

8 Pearl River Spring 13.8 14.6 0.78 0.88 70.6 71.3 0.95 0.59Summer 44.2 44.3 0.65 0.69 52.5 52.8 0.87 0.66Autumn 3.2 7.6 0.00x 0.97 60.2 60.7 0.95 0.63Winter 50.8 51.6 0.24x 2.07 69.3 70.1 0.92 0.59Annual 10.9 11.5 0.31 0.90 61.6 61.8 0.85 0.62

9 Southwest rivers Spring 43.5 43.5 0.77 1.77 81.4 81.9 0.82 0.55Summer 1.7 4.1 0.58 1.02 57.5 57.9 0.88 0.64Autumn 32.2 32.3 0.50 1.48 60.6 60.8 0.82 0.62Winter 73.8 73.9 0.51 3.84 86.8 87.3 0.86 0.54Annual 32.8 32.8 0.29 1.49 70.4 70.6 0.66 0.59

10 Northwest rivers Spring 51.7 51.9 0.33 2.08 124.30 124.70 0.92 0.45Summer 9.0 9.8 0.27x 1.10 107.90 108.20 0.91 0.48Autumn 51.2 51.6 0.04x 2.06 101.10 101.40 0.78 0.50Winter 99.9 100.20 0.25x 521.5100 86.3 87.3 0.90 0.54Annual 35.7 35.9 0.00x 1.56 109.10 109.40 0.76 0.48


10/10

Clim Res 28: 123132, 2005

only temperature as input data while, depending on

the season and region, other variables like wind speed,

humidity and solar radiation may determine the

magnitude of ET. Because the Thornthwaite method

cannot capture the spatial and temporal patterns of

ET0, its usefulness in China is questionable.(3) Pan measurement shows a systematic deviation

from the Penman-Monteith estimate, and the seasonal

and regional structures of this deviation are fairly

stable. Furthermore, the temporal variation of ET0 is

much better represented by pan measurement than by

the Thornthwaite method. The positive and high corre-

lation in time plus the consistent regional and seasonal

deviation indicate that pan measurement can be a

good substitute for the Penman-Monteith method if

appropriate corrections are made to account for the

systematic errors.

(4) The correction factors (pan coefficients) for 10

major river basins in China can be used to estimateregional ET0 from pan measurement. The annual mean

pan coefficient ranges from 0.4 to 0.8 with an average

of about 0.6 for the whole of China.

(5) In most drainage basins of China, the values of

ET0 estimated by Penman-Monteith and water evapo-

ration measured by pan have decreased in the past

50 yr. A recent study (Xu et al. 2004) shows that the

decrease in ET is the result of decrease in wind speed

and net radiation, which in turn can be attributed, to

some extent, to the increase in urban areas and air

pollution. Further study is needed to evaluate how the

decrease in ET0 affects the actual ET.

Acknowledgements. This research was supported by grants

from the Chinese Ministry of Science and Technology(2001BA611B-01), the Swedish Research Council (VR),

the Swedish Foundation for International Cooperation inResearch and High Education, Chinese Ministry of Water

Resources, Chinese Academy of Sciences and the ChinaMeteorological Administration.

LITERATURE CITED

Allen RG, Pereira LS, Raes D, Smith M (1998) Crop evapotran-

spirationguidelines for computing crop water require-ments. FAO Irrigation & Drainage Paper 56. FAO, Rome

Axel TH (2000) Spatial and temporal characteristics of poten-tial evapotranspiration trends over China. Int J Climatol

20:381396Blaney HF, Criddle WD (1950) Determining water require-

ments in irrigated areas from climatological irrigationdata. Soil Conservation Service Tech Paper No. 96, US

Department of Agriculture, Washington, DCBrutsaert W (1982) Evaporation into the atmosphere. Reidal,

Dordrecht

Brutsaert W, Parlange MB (1998) Hydrological cycle explainsthe evaporation paradox. Nature 396:30

Chattopadhyay N, Hulme M (1997) Evaporation and potential

evapotranspiration in India under conditions of recent and

future climatic change. Agric For Meteorol 87:5574Doorenbos J, Pruitt OW (1977) Crop water requirements.

FAO Irrigation & Drainage Paper 24. Land and WaterDevelopment Division, FAO, Rome

Dyck S (1983) Overview on the present status of the concepts

of water balance models. In: Van der Beken A, HerrmannA (eds) Proc Hamburg Workshop on New Approaches in

Water Balance Computations. IAHS Publ 148:319Gao GD, Lu YR, Li HJ (1978) The calculation and distribution

of maximum potential evaporation in China. Acta GeogrSinica 33:102111 (in Chinese with English abstract)

Guitjens JC (1982) Models of alfalfa yield and evapotranspi-ration. Proc Am Soc Civil Engineers. J Irr Drain Div-ASCE

108(IR3):21222Guo SL, Wang JX, Xiong LH, Ying AW, Li DF (2002) A macro-

scale and semi-distributed monthly water balance modelto predict climate change impacts in China. J Hydrol

268:115Harbeck GE (1962) A practical field technique for measuring

reservoir evaporation utilizing mass-transfer theory. Geo-logical Survey Professional Paper 272-E. Government

Printing Office, Washington, DC, p 101105Jensen ME (ed) (1973) Consumptive use of water and irri-

gation water requirements. American Society of Civil

Engineers, New YorkLiu XN, Wang SQ, Wu ZX, Wang Y (1998) Comparative

analysis on two kinds of observed evaporation data inChina. Q J Appl Meteorol 9:321328 (in Chinese with

English abstract)Lu QY, Wei L, Du ZP, Lin ZY (1965) A study of wet and dry

periods in China and a delineation of wet and dry regions.Acta Geogr Sinica 31:1524 (in Chinese with English

abstract)Ma ZG, Fu CB (2001) Trend of surface humid index in the arid

area of Northern China. Acta Meteorol Sinica 59:737746

(in Chinese with English abstract)

Monteith JL (1965) Evaporation and environment. Proc SympSoc Exp Biol 19:205234Penman HL (1948) Natural evaporation from open water, bare

soil and grass. Proc R Soc Lond 193:120145Peterson TC, Golubev VS, Groisman PY (1995) Evaporation

losing its strength. Nature 377:687688Priestley CHB, Taylor RJ (1972) On the assessment of the

surface heat flux and evaporation using large-scaleparameters. Mon Weather Rev 100:8192

Qian JL, Lin ZG (1965) A preliminary study of dry and wetclimatic regionalization in China. Acta Geogr Sinica 31:

114 (in Chinese with English abstract)

Ren ZH, Li MQ, Zhang WM (2002) Conversion coefficient ofthe small evaporation pan into the E-601B pan in China.

Q J Appl Meteorol 13:508512 (in Chinese with Englishabstract)

Thornthwaite CW (1948) An approach toward a rationalclassification of climate. Geogr Rev 38:55 94

Xu CY, Singh VP (2002) Cross-comparison of mass-transfer,radiation and temperature based evaporation models.

Water Res Manag 16:197219Zhu CH (1982) A further discussion on the climatological cal-

culating method of total radiation (II). J Nanjing Inst Mete-orol 2:196206 (in Chinese with English abstract)

Zhu GK, Yang JZ (1955) The application of meteorologicalrecords in economic construction, Part II: a preliminary

study of evaporation in various parts of China. J Meteorol

26:124 (in Chinese with English abstract)

132

Editorial responsibility: Helmut Mayer,Freiburg, Germany

Submitted: August 30, 2004; Accepted: November 30, 2004Proofs received from author(s): January 3, 2005

Date post:	03-Jun-2018
Category:	Documents
Upload:	lgtsoria
View:	228 times
Download:	0 times

Chen Et Al Methods of Estimating Evapotranspiration

Documents